Infrastructure as code, automation of software development and operations processes. Complete toolset for DevOps methodology implementation.

Infrastructure as code, automation of software development and operations processes. Complete toolset for DevOps methodology implementation.

Multi-layered infrastructure protection with DDoS defense, WAF, IAM, and cryptographic key management. 24/7 threat monitoring with automated response.

Comprehensive computing resources from virtual machines to distributed big data processing. Backup, image management, and auto-scalable Apache Spark environment.

API management, message queuing, business process automation. Tools for organizing interaction between systems with Apache Kafka and RabbitMQ support.

IoT device management for retail self-service terminals, biometric access systems, and physical security infrastructure. Real-time monitoring and remote management.

Kubernetes orchestration, serverless functions platform. Complete toolkit for containerized workloads and event-driven serverless execution.

AI-powered responsible platform models (v4), fraud detection, and user churn prediction. Custom ML models trained on your data with full GDPR compliance.

AI-powered video analytics for automated video stream analysis. Computer vision for object detection, behavior analysis, and event recognition in video content.

We analyze your requirements and regulatory obligations

Custom solution design tailored to your jurisdiction

24-72 hour deployment with zero downtime migration

24/7 monitoring and expert support team

Kubernetes — platform for automated deployment, scaling, and management of containerized applications. Multi-cluster orchestration across 180+ PoPs with automatic failover.

Tools and platforms for automating continuous integration and delivery processes. Full GitOps workflow with automatic rollbacks and canary releases across all regions.

Cloud CLI tools for managing cloud infrastructure resources via command line. Full API access with comprehensive documentation and SDK support.

Comprehensive set of tools, methodologies, and practices for organizing and automating DevOps processes. Integrated monitoring, logging, and alerting systems.

Development and testing laboratories providing controlled environments for development and testing work. Isolated environments with production-like configurations.

Management of virtual machines and computing environments for development and project support. On-demand provisioning with custom configurations.

Automation of creation, deployment, and management of all necessary infrastructure through software tools. Version-controlled infrastructure with reproducible deployments.

Automate deployment and infrastructure management processes

Ensure continuous integration and software delivery

Centrally manage containerized applications

Create and maintain necessary development and testing environments

Pre-trained artificial intelligence services designed for natural language processing tasks, including text analysis, classification, entity extraction and other text processing tasks. Ready-to-use models for immediate deployment.

Pre-trained deep learning models developed to solve complex tasks related to processing large volumes of data, such as pattern recognition, classification and forecasting. Optimized for high-performance inference across our global network.

Demand forecasting service using machine learning methods to build forecasts for goods and services demand based on historical data and other factors. Adaptive models that improve over time with your data.

Comprehensive machine learning platform providing a complete set of tools for creating, training, deploying and managing machine learning models at all stages of the lifecycle. Full MLOps support with automated retraining and monitoring.

Advanced video analytics capabilities for processing unstructured data. Real-time analysis of user behavior, responsible platform monitoring, and security surveillance with automated alerting systems.

Scalable solutions for storing and processing large volumes of structured data. Distributed storage with sub-millisecond latency, automatic sharding, and compliance with data residency requirements across 47 jurisdictions.

Interactive dashboards and business intelligence tools Real-time KPI tracking, custom report generation, and regulatory & compliance reporting for multiple jurisdictions.

Automated data pipelines for ETL processes. Real-time data ingestion, transformation, and loading with built-in data quality checks and anomaly detection.

Advanced predictive models for customer lifetime value, churn prediction, fraud detection, and responsible platform risk assessment. Models continuously updated with your operational data.

Deploy AI services immediately without training from scratch

Complete platform for managing models from development to production

Handle petabytes of data with guaranteed performance

Get actionable insights from your data in real-time

Every request is verified, even internal ones. We trust no one by default — we check everything, always.

Protection against next-generation attacks. Multi-layer security system with advanced cryptographic methods.

ML models monitor every event in the system and detect suspicious activity in real-time.

Nothing stays long — keys and certificates are automatically updated on schedule and when suspicious.

One operator never sees another's data. Physical and logical isolation at all levels.

Annual independent audits conducted by leading global audit firms — all reports available to verified, compliant partners.

Backup and recovery service designed for creating backup copies of data and computing resources, as well as restoring them when necessary. Automated backup scheduling with incremental snapshots, point-in-time recovery, and geo-redundant storage across multiple regions. Support for application-consistent backups with pre/post-scripts for databases and critical workloads.

Image management service that allows you to create, store, manage and use images of operating systems and software for rapid deployment of virtual machines and other computing resources. Golden image libraries with pre-configured OS and application stacks, version control for images, and automated security patching. Support for custom image builds with CI/CD integration.

Auto-scalable Apache Spark execution environment running on Kubernetes, purpose-built for distributed data processing, large-scale analytics, and compute-intensive workloads. Features dynamic resource allocation based on actual demand, native support for Spark SQL, MLlib, and GraphX. Seamless integration with data lakes and streaming platforms enabling real-time and near-real-time analytics.

Managed virtual machines providing computing resources in the form of virtualized servers for executing various workloads and supporting projects. Wide range of instance types from general-purpose to GPU-accelerated, available in 180+ locations worldwide. Automatic scaling, live migration with zero downtime, and SSD/NVMe storage options. Full isolation between busineses with dedicated networking and security controls.

Comprehensive backup and resource availability management

Fast infrastructure deployment using pre-configured images

Scalable platform for distributed computing and analytics

Managed VMs for any type of workload

API management service that ensures creation, publication, monitoring and lifecycle management of APIs. Allows centralized management of API access, ensuring their security and tracking usage. Full API gateway with rate limiting, authentication, request/response transformation, and analytics dashboard.

Low-code integration platform that allows creating business processes and automating interaction between different systems without writing significant amounts of code. Visual workflow designer with drag-and-drop interface, pre-built connectors for popular services, and custom integration capabilities.

Managed service for Apache Kafka clusters, designed for organizing high-performance streaming message exchange and real-time event processing. Auto-scaling clusters with multi-region replication, exactly-once semantics, and integration with analytics platforms for stream processing.

Managed service for RabbitMQ clusters, providing capabilities for organizing reliable asynchronous message exchange between different components of distributed systems. High-availability clusters with automatic failover, message persistence, and support for multiple messaging patterns (pub/sub, request/reply, work queues).

Catalog of ready-to-deploy software modules and components in the cloud environment. Simplifies rapid integration of applications, services, and third-party systems. Pre-configured connectors for leading payment processors, core business APIs, affiliate & partner marketing platforms, and automated regulatory & compliance reporting systems. 200+ certified, production-ready connectors available for immediate deployment.

Notification delivery service that allows transmitting messages through various channels (email, SMS, push notifications, etc.) within business processes and integration scenarios. Multi-channel delivery with fallback mechanisms, template management, delivery tracking, and compliance with GDPR and anti-spam regulations.

Scalable and reliable message queue system designed for asynchronous task processing and ensuring reliable message transmission between different system components. Distributed queue architecture with guaranteed delivery, message deduplication, dead-letter queues, and priority-based routing for critical operations.

Centralized API management with access control and usage tracking

Visual workflow designer for business process automation

High-performance message streaming with Kafka and RabbitMQ

200+ pre-built connectors in marketplace

High-volume IoT data storage and analytics platform built on the Apache Hadoop ecosystem. Scalable architecture designed to collect, store, and analyze petabytes of telemetry data with efficient querying and processing. Optimized for time-series workloads from retail self-service terminals, biometric access sensors, physical security devices, and other connected endpoints.

Managed Hadoop ecosystem providing capabilities for distributed processing and storage of large volumes of data from IoT devices. Built-in HDFS for reliable storage, MapReduce for batch processing, and Hive for SQL-like querying. Full integration with DS Data Lake for seamless data pipeline orchestration.

Advanced IoT data analytics service for connected devices. Enables powerful analytical workflows to extract actionable insights from high-volume telemetry streams. Real-time stream processing for instant anomaly detection, historical trend analysis for predictive maintenance, and fully customizable dashboards for operational monitoring. Pre-built analytics modules optimized for retail self-service terminal performance and user interaction patterns.

Comprehensive IoT device security solution. Provides strong authentication, authorization, and secure communication between devices and cloud infrastructure. Certificate-based device identity management, end-to-end encryption for all communications, and automated threat detection for identifying and isolating compromised devices. Compliant with ISO 27001 and applicable industry security standards for regulated digital operations.

End-to-end IoT platform from device connectivity to analytics

Bank-grade security for device communications and data

Millisecond latency for critical event processing

Machine learning models optimized for IoT data

Automated deployment, management, and scaling of containerized applications on a production-grade Kubernetes platform. Full orchestration capabilities including container scheduling, service discovery, load balancing, horizontal auto-scaling, self-healing, and advanced network management. Multi-cluster management across 180+ Points of Presence (PoPs) worldwide with a centralized control plane. Integrated monitoring, centralized logging, and enterprise security controls built in. Ideal for microservices architectures powering mission-critical digital platforms such as payment processing, real-time transaction services, high-traffic online marketplaces, and regulated digital operations. High-availability configurations featuring automated failover, geo-redundancy, and disaster recovery.

Serverless function execution platform for building, deploying, and managing event-driven applications. Compute resources are provisioned automatically only when triggered by requests or events — eliminating the need to manage servers or infrastructure. Write and deploy individual functions or lightweight code fragments that respond instantly to events, each running in complete isolation with automatic scaling from zero to thousands of concurrent executions. Supports multiple popular runtimes (Node.js, Python, Go, Java, and more), true pay-per-use pricing (you pay only for actual execution time and resources consumed), and seamless integration with message queues, databases, storage services, API gateways, and event sources. Ideal for real-time event processing, short-lived tasks, webhook handling, data transformations, background jobs, and microservices architectures where functions scale independently based on demand.

Centralized management of Kubernetes clusters across 180+ global locations. Unified control plane for deploying applications to multiple regions with automated cluster federation and cross-cluster service discovery.

Horizontal Pod Autoscaler (HPA) for automatic scaling based on CPU, memory, or custom metrics. Vertical Pod Autoscaler (VPA) for right-sizing container resources. Automatic pod restart on failure and node rescheduling for high availability.

Built-in service mesh support (Istio/Linkerd) for advanced traffic management, circuit breaking, retries, and observability. mTLS encryption between services for zero-trust security. Canary deployments and A/B testing capabilities.

Declarative configuration management with GitOps tools (ArgoCD/Flux). Automatic synchronization of cluster state with Git repositories. Full audit trail of all infrastructure changes with automated rollback capabilities.

Pod Security Policies and OPA Gatekeeper for enforcing security standards. Network policies for micro-segmentation. RBAC integration with enterprise identity providers. Automated vulnerability scanning for container images.

Integrated Prometheus for metrics collection and Grafana for visualization. Centralized logging with ELK/EFK stack. Distributed tracing with Jaeger for microservices debugging. Custom alerting rules for proactive incident management.

Trigger functions from multiple event sources: HTTP requests, message queues (Kafka, RabbitMQ), database changes, file uploads, scheduled events. Asynchronous execution with automatic retries and dead-letter queues for failed invocations.

Support for Node.js, Python, Go, Java, and .NET runtimes. Custom runtime support for specialized workloads. Pre-warmed execution environments for sub-50ms cold start times. Long-running function support for up to 15 minutes execution time.

Scale from zero to thousands of concurrent executions automatically. No infrastructure provisioning or capacity planning required. Built-in concurrency controls and rate limiting. Cost optimization with pay-per-invocation pricing model.

Local development and testing tools. CI/CD integration for automated deployments. Version control and traffic splitting for blue-green deployments. Dependency management with layer support for shared libraries.

Real-time function metrics (invocations, duration, errors, throttles). Detailed execution logs with structured logging support. Distributed tracing across function calls. Custom metrics and alarms for business KPIs.

Function-level IAM policies and role-based access control. VPC integration for private network access. Secrets management integration for credentials and API keys. Encryption at rest and in transit for all function data.

Enterprise Kubernetes with multi-cluster management across 180+ PoPs

Event-driven functions with automatic scaling and pay-per-use pricing

GitOps workflow, CI/CD integration, and local development tools

Built-in monitoring, logging, security, and compliance controls

Pre-trained AI services for natural language processing tasks. Includes text analysis, classification, named entity recognition (NER), sentiment analysis, language detection, and more. Ready-to-use, production-grade models that deploy instantly with no additional training required. Optimized for high-traffic digital platform use cases: user communication analysis, responsible platform text detection, automated customer support workflows, and review / feedback sentiment analysis. Multi-language coverage across 47 jurisdictions with continuous model updates and improvements.

Data storage designed for collecting, storing and analyzing large volumes of data for machine learning model training, using Apache Hadoop ecosystem. Petabyte-scale storage with efficient querying capabilities, optimized for structured and unstructured ML training data. Support for feature stores, versioned datasets, and data lineage tracking. Automated data quality checks and anomaly detection for training datasets. Seamless integration with DS ML Ecosystem for model training pipelines.

Pre-trained deep learning models designed for complex large-scale data processing tasks. Including pattern recognition, multi-class classification, time-series forecasting, and behavioral sequence analysis. Leveraging state-of-the-art neural network architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) units, and Transformer-based models. Ready-to-use pre-trained models for:

• responsible platform behavior detection,
• fraud & anomaly pattern recognition,
• customer lifetime value prediction,
• churn & attrition forecasting.

Full transfer learning support — easily fine-tune models on your proprietary datasets for maximum domain-specific accuracy. GPU-accelerated inference deployed across 41 global locations, delivering sub-100 ms latency for real-time predictions and decisioning.

Demand forecasting service powered by advanced machine learning. Builds precise, data-driven forecasts using historical patterns and external influencing factors. Supports multiple state-of-the-art time-series algorithms including ARIMA, Prophet, LSTM, XGBoost, and ensemble approaches. Includes automated detection of seasonality, trend decomposition, outlier handling, and seamless integration of external variables (e.g., marketing campaigns, promotions, holidays, economic indicators, regional events, or weather data).

Managed Hadoop ecosystem providing capabilities for distributed processing and storage of large volumes of data used in machine learning processes. HDFS for reliable storage of training datasets, MapReduce for batch processing of feature engineering pipelines, Hive for SQL-like querying of training data. Full integration with DS Data Lake and DS ML Ecosystem. Support for Spark SQL, Pig, and HBase for flexible data processing workflows. Automated cluster scaling based on job requirements.

Comprehensive machine learning platform providing a complete set of tools for creating, training, deploying and managing machine learning models at all stages of their lifecycle. End-to-end MLOps platform with experiment tracking, model versioning, hyperparameter tuning, and A/B testing capabilities. Integrated Jupyter notebooks for data exploration, automated feature engineering tools, and model explainability dashboards. Support for popular frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost). Production model deployment with automatic scaling, monitoring, and retraining triggers. Model registry with governance controls for compliance and audit trails. Responsible AI tools for bias detection and fairness testing.

Auto-scalable Apache Spark execution environment on Kubernetes platform, designed for distributed computing and processing large volumes of data required for machine learning tasks. Dynamic resource allocation for training jobs, support for Spark MLlib for distributed machine learning algorithms. Seamless integration with DS Data Lake for data loading and DS ML Ecosystem for model training. Optimized for feature engineering at scale, batch prediction workloads, and model retraining pipelines. Support for streaming ML for real-time model updates. GPU acceleration for deep learning training with distributed data parallelism.

Advanced machine learning models for detecting potentially harmful or at-risk user behavior. Multi-modal detection engine combining behavioral patterns, transaction analysis, session characteristics, and communication analysis. Real-time risk scoring with fully configurable thresholds per jurisdiction or regulatory framework. Seamless integration with national consumer protection databases, and responsible usage systems. Automated intervention triggers, escalation workflows, and audit-ready reporting for full regulatory compliance. Continuous model retraining using anonymized, privacy-compliant user data.

Real-time fraud detection powered by ensemble machine learning models. Account takeover detection, promotional abuse identification, payment fraud recognition, and coordinated collusion detection. Graph neural networks for uncovering fraud rings and interconnected accounts. Anomaly detection for unusual transaction patterns and suspicious activity. Achieves low false-positive rates with explainable AI outputs tailored for investigation teams. Seamless integration with leading payment processors and KYC/identity verification systems.

Advanced Predictive Models for Customer Lifetime Value (LTV) Estimation from First Interaction State-of-the-art machine learning suite delivering precise LTV forecasts starting from the initial user touchpoint.

Early Warning System for Customer Churn Risk
Production-grade predictive system designed to identify users at elevated risk of disengagement or churn well before they leave the platform, enabling timely, targeted retention interventions.

Automatic detection, recognition and classification of objects present in video streams. Real-time object tracking across frames with persistent identity. Support for custom object classes trained on your specific use cases. Multi-object detection processing hundreds of objects simultaneously per frame.

Advanced Video Analytics for Behavioral Pattern Recognition
Real-time and forensic analysis of behavior patterns, events, and individual characteristics captured in live or recorded video streams.

Automated event detection and classification from video content. Configurable event triggers with customizable thresholds. Real-time alerting for critical events. Historical event search and playback. Integration with security systems for incident response automation.

Extract structured information from unstructured video data. Scene understanding and contextual analysis. Temporal relationship detection between events. Automated tagging and metadata generation for video archives. Natural language descriptions of video content for searchability.

Process live video streams with low latency (sub-100ms). Distributed processing across 180+ PoPs for local analysis. Support for multiple simultaneous video streams per location. Automatic load balancing and failover for high availability. Edge processing capability for reduced bandwidth and faster response.

Pre-trained deep learning models optimized for high-performance digital and physical platform scenarios. Face detection and recognition (with explicit user consent and full regulatory compliance). Gesture recognition for seamless user interactions. License plate recognition for efficient parking management. Custom model training on your video data leveraging transfer learning.

Real-time security monitoring with automated threat detection. Recognition of banned individuals from self-exclusion databases (OASIS, Spelpaus, ROFUS). Detection of suspicious activities and fraud attempts. Perimeter intrusion detection for restricted areas. Integration with access control systems for automated response.

Customer traffic analysis and peak hour identification. Queue detection and wait time measurement. Staff presence verification and service quality monitoring. Facility maintenance alerts (spills, equipment issues, cleanliness). Occupancy counting for capacity management and COVID-19 compliance.

Customer demographics analysis (age group, gender distribution). Conversion rate tracking from entrance to terminal engagement. Dwell time analytics for different zones. Repeat visitor recognition (with consent). Marketing campaign effectiveness measurement through foot traffic correlation.

Simultaneous analysis from multiple camera angles with object tracking across cameras. 3D spatial reconstruction from multi-view video. Blind spot elimination through camera overlap analysis. Coordinated PTZ (pan-tilt-zoom) camera control based on detected events.

AI-powered video upscaling and denoising. Low-light enhancement for improved night vision analysis. Motion deblurring for fast-moving objects. Super-resolution for zooming into archived footage. Automatic exposure and white balance correction.

Automatic face blurring for privacy compliance (GDPR, CCPA). Zone-based privacy masking for sensitive areas. Anonymized analytics preserving insights without storing biometric data. Configurable retention policies with automatic deletion. Encrypted video storage and transmission.

ONVIF protocol support for camera compatibility. RTSP/RTMP stream ingestion. Webhook notifications for detected events. RESTful API for programmatic access. SDK for custom application development. Integration with DS IoT Platform for unified device management.

Process thousands of concurrent video streams. Distributed GPU processing across 41 global locations. Automatic scaling based on video stream load. Frame rate prioritization for critical cameras. Bandwidth optimization through edge processing and intelligent streaming.

Semantic search across video archives ("find person wearing red jacket"). Time-based search with calendar interface. Event-based search (all instances of detected events). Object-based search (find all appearances of specific object). Export capabilities for investigation and compliance.